Identification of a Human Immunodeficiency Virus Type 1 and Neurosyphilis Cluster in Vermont

Public health officials and clinicians in Vermont discovered a cluster of neurosyphilis cases among newly diagnosed individuals living with human immunodeficiency virus type 1 in 2017-2018, largely among men who have sex with men. This prompted a coordinated investigation to better characterize sexual networks and phylogenetics. Background Rates of syphilis in the United States have more than doubled over the last several decades, largely among men who have sex with men (MSM). Our study characterizes a cluster of neurosyphilis cases among people with human immunodeficiency virus 1 (HIV-1) in Vermont in 2017-2018. Methods Vermont Department of Health disease intervention specialists conduct interviews with newly diagnosed HIV-1 cases and pursue sexual networking analyses. Phylogenetic and network analyses of available Vermont HIV-1 polymerase (pol) sequences identified clusters of infection. Fishers-exact and independent t-tests were used to compare people with HIV-1 within or outside an identified cluster. Results Between 1 January 2017 and 31 December 2018, 38 residents were diagnosed with HIV-1 infection. The mean age was 35.5 years, 79% were male and 82% were White. Risk factors for HIV-1 included MSM status (79%) and methamphetamine use (21%). Eighteen cases (49%) had HIV-1 viral loads (VLs) >100 000 copies/mL and 47% had CD4 cell counts <200/mm(3). Eleven of the 38 (29%) had positive syphilis serology, including four (36%) with neurosyphilis. Sexual networking analysis revealed a ten-person cluster with higher VLs at diagnosis (90% with VLs > 100 000 copies/mL vs 33%, P = 0.015). Phylogenetic analysis of pol sequences showed a cluster of 14 cases with sequences that shared 98%-100% HIV-1 nucleotide identity. Conclusions This investigation of newly infected HIV-1 cases in Vermont led to identification of a cluster that appeared more likely to have advanced HIV-1 disease and neurosyphilis, supported by phylogenetic and network analyses.